Pothole Detection Using Deep Learning Classification Method
Objective
The main objectives of this project are to detect and classify potholes on roads using deep learning-based image classification methods.It analyzes road surface images to identify cracks, depressions, and pothole severity with high accuracy. This solution supports timely road maintenance and enhances safety in transportation infrastructure.
Abstract
This project presents a smart pothole detection system using Raspberry Pi, YOLOv8, camera module, LCD display, buzzer, GSM, GPS, DC motor, and relay module. The system detects potholes in real time using deep learning image processing techniques. When a pothole is detected, the buzzer alert is activated, and the warning message is displayed on the LCD screen. The GPS module tracks the pothole location, while the GSM module sends alert messages for monitoring purposes. The proposed system improves road safety, reduces vehicle damage, and provides an efficient low-cost solution for intelligent transportation systems.
Keywords: YOLOv8, Raspberry Pi, Pothole Detection, Deep Learning, GSM Module, GPS Module, LCD Display, Camera Module, Buzzer Alert, Relay Module, Smart Transportation, Road Safety, Real-Time Detection.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Hardware components:
- Raspberry pi
- memory card
- LCD
- Web camera
- Buzzer
- GSM
- GPS
- Relay
- DC Motor
- connectors-10
Software requirements:
- Raspbian os
- Python
Learning Outcomes
- Raspberry Pi pin diagram and architecture
- How to install Raspberry Pi OS / setup software
- Setting up and installation procedure for Raspberry Pi
- Introduction to Raspberry Pi environment / development setup
- Basic programming in Raspberry Pi (Python / C / C++)
- Basics of Embedded programming using Raspberry Pi
- Basics of IoT platforms
- Working of power supply
- About Project Development Life Cycle:
- Planning and Requirement Gathering (software, tools, hardware components, etc.)
- Schematic preparation
- Code development and debugging
- Hardware development and debugging
- Development of the project and output testing
- Practical exposure to:
- Hardware and software tools
- Solution providing for real-time problems
- Working with team/individual
- Work on creative ideas
- Skills developed:
- Project development skills
- Problem analyzing skills
- Problem solving skills
- Creativity and imaginative skills
- Programming skills
- Deployment
- Testing skills
- Debugging skills
- Project presentation skills
- Thesis writing skills
Paper Publishing
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Disclaimer - Takeoff Edu Group Projects are not associated or affiliated with IEEE in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, not projects of or by IEEE.
